Over-exploitation of groundwater resources often causes seawater to intrude into coastal aquifers. This study aims to evaluate how different beach slopes (90 degrees, 75 degrees, 60 degrees, and 45 degrees) affect the extent and behavior of seawater intrusion in unconfined coastal aquifers under transient conditions. A threedimensional laboratory model was constructed to simulate seawater intrusion under varying beach slopes. Experimental data were analyzed using image processing techniques, and results were validated using the SEAWAT numerical model. Key parameters-including wedge toe length, height, and area-were measured over time to assess the transient response of the saltwater wedge. The results showed that under static conditions, flatter slopes produced larger saltwater wedges. During transient conditions following a groundwater-level decline, the wedge toe advanced approximately 57% further in the vertical slope than in the 45 degrees slope, while the final wedge size remained smaller on the steeper beach. The wedge height stabilized earlier than the toe length and area during intrusion, whereas in the recession stage, all three indices reached equilibrium almost simultaneously. The geometry of the beach slope has a significant effect on both the extent and temporal behavior of seawater intrusion. The toe length index showed a strong relationship with wedge area and can serve as a reliable indicator of intrusion volume under both steady and transient conditions. These findings emphasize the importance of considering beach slope in the design and management of coastal aquifer systems. Understanding how slope geometry influences the evolution of the saltwater wedge can improve the prediction and control of seawater intrusion in response to groundwater-level fluctuations.

A qanat, an ancient engineering technique known as a sustainable groundwater resource, helps humans to abstract water from underground for agriculture and drinking in arid countries like Iran. Regretfully, a portion of qanat’s water is wasted during non-crop seasons. To overcome this issue, ancient Iranians constructed underground dams within the qanats to trap water under the ground and control the flowrate. This study employs a meshless numerical method, namely MLPG, to investigate the effects of underground dam construction on a qanat in Birjand unconfined aquifer. The qanat, known as Haji-Abad, is one of the most famous in this region. Two scenarios are considered: one without an underground dam and one with an underground dam. In the first scenario, the groundwater level is simulated over 5 years (2018–2023) and its fluctuations are drawn for the nearest piezometers of the qanat. The results show a decreasing trend in the groundwater level in all piezometers. For example, piezometers #1, #2, #3 and #4 present drawdowns of 4.59 m, 2.05 m, 3.43 m and 3.27 m, respectively, during the simulation period. In the second scenario, the groundwater level with considering an underground dam is recalculated. In piezometer #1, which is the closest to the considered location of the underground dam, the groundwater level shows a slight increase after 41st month of modeling. It means that the underground dam contributes to recharge the aquifer and by injecting water into it. The total injected volume of water during this period (41–60th month) is 1,008,750 m3. This value is meaningful for Birjand aquifer, demonstrating that construction of underground dams on qanats in this aquifer is a beneficial practice.

Sustainable management of groundwater resources, as a multifaceted challenge in water sciences, necessitates the adoption of novel computational approaches for monitoring, modeling, and predicting dynamics. This research investigates the status and outlines future research directions in advanced remote sensing applications for groundwater management from 2000 to 2024. Data extracted from the Web of Science Core Collection database (n=2356) were analyzed using the Bibliometrix package in the R environment. The results reveal a significant growth in the research field, with GRACE satellite data recognized as a key indicator in assessing groundwater storage changes. Furthermore, the emergence of "land-surface model" and "risk assessment" concepts reflects a trend towards integrated modeling and comprehensive risk evaluation. The integration of multi-source remote sensing data (including data from new-generation satellites and aerial platforms) with advanced artificial intelligence algorithms (such as deep neural networks, physics-informed models, and reinforcement learning methods) is expected to become a central focus for leading researchers in hydrology, water resources, and machine learning engineering. This convergence will pave the way for developing more reliable prediction models, accurate uncertainty analysis, and the provision of optimal groundwater resources management solutions under various climatic and land-use scenarios. This bibliometric analysis, by systematically reviewing the research published in reputable scientific databases, provides an overview of the status, emerging trends, and future priorities in this vital field for the scientific community.

Releasing the effluents of urban wastewater treatment plants (UWTP) downstream especially in populated areas, can negatively affect the surface water, groundwater quality. A new method, Multi soil layering (MSL) ecotechnology introduced last few decades, a cost-efficient treatment system can reduce those negative issues. In this study, three MSL systems were developed to UWTP effluent released in environment. Zeolite and for the first time silica materials were used in the permeable layers. Clay soil and for the first time waste stone powder from the stone factory with iron filing, sawdust and charcoal were used in soil mixture layers to investigate the ability of different friendly materials on the pollutant removal rate in the MSL ecotechnology. The material properties were determined using X-ray diffraction (XRD), X-ray fluorescence (XRF), scanning electron microscopy (SEM), Brunauer-Emmett-Teller (BET) surface area analysis, contact angle measurement, surface roughness analysis, Thermogravimetry (TG) and Fourier-transform infrared spectroscopy (FTIR) analyses. The results proved the performance of MSLs and the effectiveness of the materials used. The highest removal rates of COD and BOD5 were 67.5% and 80% respectively in MSL-1 system, while PO43− and NO3− were 99% and 80% respectively in MSL-3 system. Result showed MSL system could reduce metal ions Cr6+, Pb2+ and Hg2+. The results also indicated that a lower contact angle or higher surface roughness does not necessarily imply better wettability and consequently better treatment performance of the materials.

As sustainable groundwater resources that provide a safe and clean water supply, qanats should be protected from pollution. For this purpose, this article introduces a new concept called the "quality border" or "quality harim." This concept acts as a boundary and determines the safe area around the qanat system in terms of contamination risk. Construction or any other activities in this area that produce pollution can enter the groundwater and get into the qanats' water, polluting it. Therefore, it is necessary to delineate this area for all qanats and prevent construction or other activities inside it. In this study, with the meshless local Petrov-Galerkin numerical method, the quality harim is determined for two qanats in the Birjand aquifer. These two qanats are selected according to the DRASTIC index map, which shows high contamination vulnerability for these qanats. Haji-Abad and Nasr-Abad are the two selected qanats with flow rates of 50 l/s and 5 l/s, respectively. The meshless local Petrov-Galerkin numerical method is then used to simulate groundwater flow in this aquifer. In the next step, to obtain the quality harim, the transport equation is solved by this numerical method in the Birjand aquifer. There are two time steps considered: 5 years (2016) and 11 years (2022). The results show that the quality harim in 2022 for the two qanats is wider than in 2016 due to groundwater drawdown and urbanization. The findings also state that both quality harims are influenced by construction, and this increases the contamination risk for both.

The problems of artificial groundwater recharge in desert areas include low rainfall and limited water resources, deposition of large amounts of sediment and high evaporation rates. In this study, an attempt has been made to mitigate these issues by introducing a new method of artificial recharge specifically designed for desert areas. For this purpose, a physical model was constructed. Through multiple experiments, which involved varying parameters such as input flow rate, materials used to construct the unsaturated environment, and changes in the depth and width of the infiltration trench, a new artificial feeding method was presented. An empirical equation was also proposed, aiming to estimate the infiltration capacity from the trench. Examination of nine earthen channels showed that the Davis and Wilson, Molesworth, Moritz and Ingham equations are not accurate for estimating water leakage in different areas. To solve this problem, the researchers adjusted the equations with regional correction coefficients. The results showed that the equation presented with the features considered in it has a significant accuracy in estimating the amount of leakage compared to real data and can also be used in different areas.

Due to the growth of population and industrial advancements in Iran, especially Birjand, the use of groundwater makes the aquifer’s balance becomes negative. This negatively affects both quantity and quality conditions of groundwater. To prevent this, suitable water management is necessary for Birjand aquifer. In this study, to overcome negative groundwater balance, the concept of “adjustment factors” is presented. These factors are applied to all types of consumption and make the groundwater balance to be positive. For this aim, a dynamic model of groundwater resources in Birjand aquifer is created in Vensim software. This model helps to determine the groundwater balance. Then, with using dynamic model and particle filter approach in MATLAB software, minimum adjustment factors are achieved. All data and information of Birjand aquifer between 2004 and 2021 are entered into Vensim model; then, under three scenarios, the groundwater balance is computed for the next 5 years (2022–2026). Three scenarios are normal, dry, and wet conditions. In the next step, with the help of particle filter, the minimum adjustment factors for two types of consumptions including agricultural and industrial are computed. The results show that the adjustment factors for all consumptions in dry conditions are much higher than others. For instance, in 2026, the adjustment factor for agriculture in dry conditions is 0.081 while in normal and wet conditions is 0.75 and 0.031, respectively. Also, the findings indicate that applying these adjustment factors to groundwater model has successful results and make the groundwater balance to be positive.

In this research, modeling and estimation of dew point temperature values ​​in eight meteorological stations located in the eastern regions of Iran were done. These stations, including Bam, Birjand, Iranshahr, Kerman, Mashhad, Tabas, Zabol and Zahan, are all characterized by a dry climate. First, the correlation of different weather parameters with dew point temperature was investigated and then the parameters of mean temperature, maximum temperature and minimum temperature were selected as the parameters with the highest correlation to dew point temperature. These selected parameters then incorporated into a VAR (Vector Autoregression) model as inputs for estimating dew point temperature values. This modeling approach allows us to capture the interdependencies between these variables and enhance our accuracy in predicting dew point temperature. Then the stability of the residual series of the VAR model was investigated and the residual series of this model was developed using the generalized ARCH model. The result of the development of the VAR model was the investigation of the dew point temperature in eight meteorological stations with the VAR-GARCH model. The results indicated that this combined model outperformed VAR model in both the train and test phases. Specifically, the VAR-GARCH model demonstrated higher accuracy and improved results compared to solely using a VAR model. The incorporation of GARCH allowed better modeling of the residual series, leading to an overall increase in accuracy ranging from 5% to 30% during the test phase. These findings suggest that considering both autoregressive dynamics and conditional heteroskedasticity is crucial for accurately predicting dew point temperatures. By incorporating GARCH into our modeling approach, we were able to capture additional information about volatility and further enhance our predictions.

Groundwater modeling is often associated with uncertainties due to incomplete knowledge of the subsurface system or uncertainties arising from variability in model system processes and field conditions. So far, not much research has been conducted to investigate the uncertainty of the groundwater flow model. Studies in this field focus on statistical methods. Due to the need to investigate the uncertainty to obtain reliable results, this study presents an approach to evaluate the uncertainty parameters of the groundwater flow model. In this way, modified GLUE (MGLUE) method as the uncertainty assessment method is linked to the meshless local Petrov–Galerkin (MLPG) as the simulation model. The method (which is called MGLUE-MLPG) is applied to two aquifers. In the first aquifer, three parameters of the meshless flow model (parameters related to the numerical method e.g., sizes of the integration and weight subdomains and the amount of the penalty coefficient) are identified as uncertainty parameters. The results indicate that these three parameters have a high degree of uncertainty, so their coefficients of variation are 72.37, 19.92 and 51.55, respectively. In the second standard aquifer, in addition to the numerical parameters, the transmissivity coefficients (model parameters) in two different directions (horizontal and vertical directions) are taken into account in the uncertainty model. The results show more uncertainty for the numerical parameters and do not show many changes in the transmissivity coefficient parameter. This means that the box diagrams of these parameters are almost the same. After precise values have been reached, groundwater flow was simulated. The obtained results are so accurate as to indicate the importance of using this model for all aquifers. In the first aquifer, the root mean square error (RMSE) values for MGLUE-MLPG and finite element method (FEM) are 0.236 and 0.249 m, respectively. The second aquifer shows higher accuracy than the other numerical method, so the RMSE values for MGLUE-MLPG and PPCM are 0.0060 and 0.0121 m, respectively.

Accurate prediction of wastewater effluent parameters is crucial for evaluating the performance of wastewater treatment plants, as it significantly contributes to reducing time, energy, and costs. This study employed three machine learning algorithms such as Artificial Neural Network (ANN), Support Vector Machine (SVM), and Gaussian Process Regression (GPR) in order to forecast the output COD values of Wastewater Treatment Plant No. 1 in Parkand Abad, Mashhad, Iran. The input data for the models included BOD5, COD, TSS, Temprature, and pH of influent sewage, recorded daily from March 2018 to June 2019. The findings indicated that the SVM model surpassed the ANN and GPR models in predicting effluent COD parameters across all three phases, with GPR also performing better compared to ANN throughout the training, validation, and testing stages. The SVM model achieved values of r = 0.82, R2 = 0.67, RMSE = 19.02, MAPE = 0.069, and MAE = 13.26 during the training phase, and the model exhibits values of r= 0.74, R2= 0.45, RMSE=28.02, MAPE=0.080, and MAE=18.46 in the testing phase.

The structural health of a pipeline is usually assessed by visual inspection. In addition to the fact that this method is expensive and time consuming, inspection of the whole structure is not possible due to limited access to some points. Therefore, adopting a damage detection method without the mentioned limitations is important in order to increase the safety of the structure. In recent years, vibration -based methods have been used to detect damage. These methods detect structural defects based on the fact that the dynamic responses of the structure will change due to damage existence. Therefore, the location and extent of damage, before and after the damage, are determined. In this study, fuzzy genetic algorithm has been used to monitor the structural health of the pipeline to create a fuzzy automated system and all kinds of possible failure scenarios that can occur for the structure. For this purpose, the results of an experimental model have been used. Its numerical model is generated in ABAQUS software and the results of the analysis are used in the fuzzy genetic algorithm. Results show that the system is more accurate in detecting high -intensity damages, and the use of higher frequency modes helps to increase accuracy. Moreover, the system considers the damage in symmetric regions with the same degree of membership. To deal with the uncertainties, some error values are added, which are observed to be negligible up to 10% of the error.

Qanat is an ancient water harvesting technology which is used for irrigation, agriculture and drinking in many countries of the world. A key element of preserving this heritage is calculating the protection area of them. In this study, the main aim is depiction of the hydraulic harim of qanat with the usage of the meshless numerical method. Afterward, the qanat package has been added to this model to delineate the hydraulic harim of the qanat. Two qanat systems are shown here, one in a standard aquifer and the other in a real test case, namely Haji-Abad qanat, located in the Birjand unconfined aquifer. In the real test case, the hydraulic harim of Haji-Abad qanat with 10 collection shafts is depicted in 3-time sections as well. The time sections are 3 years after extraction (2014), 6 years (2017) and 11 years (2022). The findings stated that time makes the harim area larger. In addition, the hydraulic harim is extended to areas with a higher hydraulic conductivity coefficient. Ultimately, we have delineated the hydraulic harim for 2040 and unfortunately, it is influenced by buildings. Therefore, it is necessary to find the hydraulic harim of qanats in order to protect this traditional heritage.

Nowadays, infiltration tactics are widely used to manage storm water in urban areas. These techniques are used and recognized around the world due to their benefits, such as reducing the negative consequences of urbanization, reducing storm water flow in sewage systems and recharging groundwater. Richards equation is one of the most well-known equations for simulating water infiltration in soil in the unsaturated area. In the present study, a one-dimensional approach to the numerical solution of Richards equation is presented using meshless Petrov–Galerkin method and Kirchhoff transformation. The results of this modeling have been compared with analytical solution, laboratory data, and finite difference and meshless numerical methods. Given that the proposed model can provide an accurate representation of water level changes in unsaturated soil compared to analytical solution, laboratory data, finite difference method and MQ-RBF with the root mean square error equal to 0.09, 1.02, 0.7 and 0.1, it can be claimed that the model can model the flow of water infiltration in unsaturated soil.

The importance of the optimal and efficient use of all available water resources becomes noticeable when today due to successive droughts and a decrease in rainfall, the surface water resources are running out. Runoff and surface water resources are some of the primary and vital available water resources, and hence, modeling and predicting their behavior are especially critical. In the current research, the aim was to model the stream flow of the Chehel Chai watershed in Golestan province, Iran, using the data of the stream flow and precipitation for a period of 45 years. For this reason, 4 machine learning algorithms namely, Extreme Learning Machine (ELM), Random Forest (RF), Gaussian Process Regression (GPR), and Gene Expression Programming (GEP) were used. The data were entered into the modeling in the form of different scenarios consisting of the stream flow and precipitation with varying lags of time. The results showed that scenario M2 (using only stream flow data with two time lags) in the ELM (extreme learning machine) model with the values of RMSE (root mean square error) =0.984 (m3/s) and R2=0.613 had the most accurate performance and predictions among all the models and scenarios.

Qanat is an ancient water harvesting technology which is used for irrigation, agriculture and drinking in many countries of the world. A key element of preserving this heritage is calculating their protection area. In this study, the main aim is depiction of the hydraulic harim of qanat with the usage of the meshless numerical method. Afterward, the qanat package has been added to this model to delineate the hydraulic harim of the qanat. Two qanat systems are shown here: one in a standard aquifer and the other in a real test case, namely Haji-Abad qanat, located in the Birjand unconfined aquifer. In the real test case, the hydraulic harim of Haji-Abad qanat with 10 collection shafts is depicted in 3 time sections as well. The time sections are 3 years after extraction (2014), 6 years (2017) and 11 years (2022). The findings stated that time makes the harim area larger. In addition, the hydraulic harim is extended to areas with a higher hydraulic conductivity coefficient. Ultimately, we have delineated the hydraulic harim for 2040 and unfortunately, it is influenced by buildings. Therefore, it is necessary to find the hydraulic harim of qanats in order to protect this traditional heritage. HIGHLIGHT This method is applicable for all qanats with different conditions.;

In the present study, the optimal place to excavate extraction wells as the drawdown gets minimized was investigated in a real aquifer. Meshless local Petrov-Galerkin (MLPG) method is used as the simulation method. The closeness of its results to the observational data compared to the finite difference solution showed the higher accuracy of this method as the RMSE for MLPG is 0.757 m while this value for finite difference equaled to 1.197 m. Particle warm algorithm is used as the optimization model. The objective function defined as the summation of the absolute values of difference between the groundwater level before abstraction and the groundwater level after abstraction from wells. In Birjand aquifer which is investigated in transient state, the value of objective function before applying the optimization model was 2.808 m, while in the optimal condition, reached to 1.329 m (47% reduction in drawdown). This fact was investigated and observed in three piezometers. In the first piezometer, the drawdown before and after model enforcement was 0.007 m and 0.003 m, respectively. This reduction occurred in other piezometers as well.

Due to the fact that ecosystems are more fragile and sensitive in arid and semi-arid regions of the world, the phenomenon of floods and the resulting damage and loss will be more severe in these areas. The subject of river canals and their morphology is one of the key topics in engineering and river management, which can be used to obtain a useful set of information about the geometric shape, bed shape, longitudinal profile, cross sections, over time. Default geometric relationships in hydrological models such as Kineros2 are based on field measurements in US watersheds and cause uncertainty in model results. Therefore, the purpose of this study is to determine the regional statistical relationships between the width and depth of the canal with the area of the upstream watersheds for employing in hydrological models such as Kineros2, and the width and depth of the canal with other basin characteristics. The data in this research are mainly topographic maps of Neishabour Bar watershed. Thus, according to topographic maps, preliminary studies were carried out to identify sub-basins. In this study, the basin is divided into 34 sub-basins that involve Lar Formation (in 16 sub-basins), and marl (in 18 sub-basins), where, 27 sub-basins in upstream are non-orchard lands. The linear and nonlinear regressions and equations were studied and evaluated using the software such as Excel, SPSS, Curve Expert, and XLSTAT. The results of correlation of physical parameters with canal width and depth, nonlinear regression analysis and analysis of variance in the relationships between canal depth/width with upstream area in the whole basin (R2=0.58 for canal depth and R2=0.14 for canal width), in upstream Lar formation, in downstream and non-orchard lands, showed a greater impact of the upstream acreage on the canal depth relative to the width (due to the higher coefficient of determination and less error). Furthermore, the separation of sub-basins in terms of geological formation and the presence of orchards had a significant effect on improving equations and reducing errors. The greater impact of the canal depth than the width from the upstream area is mostly related to successive droughts and the absence of flash floods in the area to change the canal depth, while the width of the canals has been mainly a function of human manipulations on the river bed. Stepwise linear regression analysis also showed a higher correlation between canal depth than the canal width with the physical parameters of the basin (R2=0.85 and R2=0.77, respectively).

Currently, one of the solutions to improve the decline in the water table of aquifers owing to their uncontrolled extraction is artificial recharge schemes, especially in arid and semi-arid regions. The present study applies a nonuniform rational B-spline functions (NURBS) based isogeometric method to investigate the effects of an injection well on the rise of water table, unconfined aquifer hydrodynamic parameters and injection rate. Also, the best injection rate was determined by linking the isogeometric analysis (IGA) simulation model to the particle swarm optimization (PSO) model. Initially, the IGA method was implemented to simulate a water table over an unconfined aquifer with two extraction wells with discharges of 1142.85 and 1428.57 m 3 day −1 for 210 days and was compared with the Modflow model. The model was tuned and run by constructing an injection well with 8214.28 m 3 day −1 injection rate for 1500 days. The IGA simulation results with ME = −0.0096, MAE = 0.0111 and RMSE = 0.0146 indicated the accuracy of the model in water table simulation compared with the Modflow model with ME = −0.0188, MAE = 0.023 and RMSE = 0.0284. The findings revealed that the use of an injection well has a positive impact on raising the water table, with a rise of 1.24 m in the observation well. Investigating the effect of the parameters on the water table changes indicated that the injection rate directly affects changes in the water table. The water table rises by more than 43% with a 50% increase in the injection rate. Also, compared with the effect of the injection rate on the water table, the transmissivity and specific yield effects were not substantial. The results of IGA–PSO showed that the best value of injection rate is 2000 m 3 day −1 , whereby the aquifer water table rises by an average of 37.12 cm.

Determination of wells’ capture zones is one of the most remarkable issues that should be carried out in each aquifer. Methods used for depicting this area has been divided into two simple and complex method. Through the simple one several mathematical equations are used and in the complex approaches, numerical models are applied. In this study, the capture zone of extraction wells in a confined aquifer is determined using random walk algorithm and finite element numerical model. The studied aquifer consists of three extraction wells and one injection well in which the extraction and injection operation are performed for 10,000 days. After the simulation procedure, the groundwater head is obtained. Simulation results show high accuracy which its root mean square error is 0.141 m while this value for finite difference solution is 0.249 m. then the capture zone for each well was depicted individually in two periods of 50 and 180 days. Results showed that the extension of the capture zone for all three wells is toward the part of the aquifer, which has a higher groundwater level than other areas. Also, the results revealed that, in areas of the aquifer that have a higher transmissivity coefficient, the zone is more extended and for the areas with lower transmissivity coefficient, its width decreased and became narrower. In the second well, the width of capture zone in zone 2 and 3 were 302.86 m and 267.46 m, respectively.

Due to the difficulty in measurement of transverse velocity in floods, it is necessary to use appropriate models for this aim. Hydrodynamic complexity of the flow in the middle of the flood is another reason for usage of precise models. Accurate prediction of flows is very difficult due to the complexity of its nature and the lack of accurate data. Here, two-dimensional modeling of the flood has been done using the finite element method (FEM). The case study is a real field river. The achieved results from the finite element model are compared with the observational data at three stations. In order to evaluate the model performance, the root mean square error (RMSE) is calculated. The relative error and the RMSE are 0.143 and 0.229 m, respectively. This amount of value indicates the high accuracy of the proposed model. In addition, computational cost including time spending and efficiency of FEM is satisfactory and this model can be used as a good tool for flow simulation.